The Wilks’ lambda value (0.116) indicated that the two discriminant functions were highly significant ( p < 0.0000), meaning that 11.6% remained unexplained (see Supplementary SDA Tables ).
Excerpts
After applying the first difference, all variables display strong evidence of stationarity, with all four test statistics highly significant ( p -values = 0.00). 4.2.
The Wilks’ lambda value (0.0000) indicates that the three discriminant functions were highly significant ( p = 0.0000), meaning there was 0% unexplained (see Supplementary SDA Tables ).
The results show a highly significant effect of the storage time on weight loss (ANOVA, F 6, 209 = 57.64, p = 0.000), moisture content of fruits (ANOVA, F 6, 209 = 36.96, p = 0.000), mass of fruits (ANOVA, F 6, 209 = 2.33, p = 0.034), firmness of fruits (ANOVA, F 6, 209 = 7.41, p = 0.000), sphericity of fruits (ANOVA, F 6, 209 = 11.93,
The lowest C22 value was found in the fifth sampling of Itrana (0.14 mg/kg), whereas the very highly significant highest value ( p = 0.000) was in the fourth sampling of Sinopolese (16.93 mg/kg) which showed a different alkane profile with respect to the other studied cultivars ( Table S2 ).
As expected, the culinary oil x time-point first-order interaction effect was also extremely significant for all oils tested ( p < 10 −50 to <10 −18 ), and this ratifies the contrasting responses of each oil type to increasing LSSFE lengths; for example, differential rates and extents PUFA losses from soybean/corn oils and extra-virgin olive/avocado oils ( Figure S1b ), and likewise the contrasting elevations and reductions in oil MUFA contents for these two groups respectively ( Figure S1a ).
The statistical analysis showed a highly significant evolution of the sugar ( p < 2 × 10 −16 ) and starch ( p < 1.339 × 10 −5 ) curves in function of the reaction time.
Conversely, the variety has a very highly significant effect ( p = 9 × 10 −13 ) on the intercepts of these relationships.
The Rao & Scott-adjusted Pearson chi-square test indicated a highly significant effect of age on food purchases driven by security needs (food stocks), F [6.67; 7068.99] = 6.28, p = 4.04 × 10 −7 .
Specifically, its intercept was highly significant ( p = 9.32 × 10 −7 ).
Variance analysis of the response surface revealed that the significance of the TFC was influenced by the percentage of ethanol, which was extremely significant ( p < 0.0000014).
A highly significant sessional variation ( p < 0.00001) was pointed out.
The results presented in Table 3 showed a highly significant ( p value = 0.00005, detection limit of the method being approximately 1 log CFU, CI-95%, 1.85, 2.77) log reduction (2.31) in microbial load after wiping the meat surface with the developed DW (count before treatment—5.48 log CFU/cm 2 ; after treatment—3.17 CFU/cm 2 ).
Analysis of variance (ANOVA) indicated that both models were highly significant ( p < 0.0001), with non-significant lack-of-fit terms ( p > 0.05).
A quadratic regression model (Equation (4)) was developed to relate the response variable to the independent factors. (4) Y = 67.75 + 0.96 A + 2.43 B − 0.34 C + 1.32 AB − 0.20 AC + 1.38 BC − 0.80 A 2 − 3.68 B 2 − 0.25 C 2 The developed model was highly significant ( p < 0.0001, Table 4 ).
One-way ANOVA revealed highly significant differences among extraction methods for all phytochemical and antioxidant parameters ( p < 0.0001; Table 2 ), confirming that extraction technology is a critical determinant of bioactive compound recovery from blackthorn berries [ 29 ].
By day 5, inhibition of Alternaria alternate and Aspergillus niger was highly significant (**** p < 0.0001), and that of Penicillium sp. was also strongly significant (*** p < 0.001), underscoring the sustained efficacy of the microencapsulated formulation.
Pearson’s correlation analysis ( n = 45) showed a powerful and highly significant positive correlation between daily As intake and the hazard index (r = 0.97, p < 0.0001), indicating that arsenic is the primary contributor to HI from the consumption of these dietary supplements.
Establishment of Regression Equation Model and Significance Test Response-surface analysis ( Tables S2 and S3 ) yielded a highly significant model ( p < 0.0001) with non-significant lack of fit ( p = 0.1273), indicating that only random error contributed to residuals.
Analysis of variance (ANOVA) and significance testing ( Table S6 ) indicate both regression models are highly significant ( p < 0.0001) with a non-significant lack of fit.
Fer-1 demonstrated a marked restoration of cell viability with a highly significant statistical difference (F(3,8) = 59.18, p < 0.0001; Figure 2 D).
As shown in Table S10 , the model had F = 10.65 and was highly significant ( p < 0.0001), while the lack of fit was not significant ( p = 0.0652 > 0.05).
The ANOVA results for protein content in this group showed a highly significant F-value of 284.19 ( p < 0.0001), demonstrating that there are statistically significant differences among the samples in this group.
In all cases, the values of p were highly significant ( p < 0.0001).
The data indicate that the regression model is highly significant ( p < 0.0001), while the error term is not significant ( p > 0.05).